I am a computational neuroscientist applying machine learning and advanced statistical methods to investigate neural dynamics during transitions in conscious state. My research focuses on the use of both surgically-implanted sEEG/ECoG and non-invasive scalp EEG recordings in humans during sleep and anesthesia to better understand the dynamical changes that underpin and track conscious states. In my teaching role, I have contributed to the inclusion of Generative AI tools into Penn's doctoral-level quantitative neuroscience coursework. I am keenly interested in scientific entrepreneurship and biomedical innovation, and have undertaken training in Finance, Management, and Entrepreneurship alongside my technical and scientific education. I am particularly interested in translational applications of neurotech and neuroinformatics.